MuPD is a pretrained generative foundation model using a diffusion transformer with cross-modal attention that synthesizes histopathology images from text or RNA data and outperforms task-specific models on generation, augmentation, and virtual staining tasks.
arXiv preprint arXiv:2407.00203 , year=
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The paper maps agent memory research via three forms (token-level, parametric, latent), three functions (factual, experiential, working), and dynamics of formation/evolution/retrieval, plus benchmarks and future directions.
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A Generative Foundation Model for Multimodal Histopathology
MuPD is a pretrained generative foundation model using a diffusion transformer with cross-modal attention that synthesizes histopathology images from text or RNA data and outperforms task-specific models on generation, augmentation, and virtual staining tasks.
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Memory in the Age of AI Agents
The paper maps agent memory research via three forms (token-level, parametric, latent), three functions (factual, experiential, working), and dynamics of formation/evolution/retrieval, plus benchmarks and future directions.